---
library_name: transformers
language:
- multilingual
license: apache-2.0
base_model: openai/whisper-tiny.en
tags:
- generated_from_trainer
datasets:
- arkanalexei/bisix_su_id_reset
metrics:
- wer
model-index:
- name: 'BisiX: Sundanese Whisper (Fine Tuned)'
  results:
  - task:
      name: Automatic Speech Recognition
      type: automatic-speech-recognition
    dataset:
      name: SU ID ASR
      type: arkanalexei/bisix_su_id_reset
      config: su_id_asr_source
      split: validation
      args: su_id_asr_source
    metrics:
    - name: Wer
      type: wer
      value: 11.164044943820224
---

<!-- This model card has been generated automatically according to the information the Trainer had access to. You
should probably proofread and complete it, then remove this comment. -->

# BisiX: Sundanese Whisper (Fine Tuned)

This model is a fine-tuned version of [openai/whisper-tiny.en](https://huggingface.co/openai/whisper-tiny.en) on the SU ID ASR dataset.
It achieves the following results on the evaluation set:
- Loss: 0.1520
- Wer: 11.1640
- Cer: 5.3914

## Model description

More information needed

## Intended uses & limitations

More information needed

## Training and evaluation data

More information needed

## Training procedure

### Training hyperparameters

The following hyperparameters were used during training:
- learning_rate: 5e-05
- train_batch_size: 32
- eval_batch_size: 16
- seed: 42
- gradient_accumulation_steps: 2
- total_train_batch_size: 64
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- lr_scheduler_warmup_steps: 30
- training_steps: 270
- mixed_precision_training: Native AMP

### Training results

| Training Loss | Epoch  | Step | Validation Loss | Wer     | Cer     |
|:-------------:|:------:|:----:|:---------------:|:-------:|:-------:|
| 3.1855        | 0.1765 | 30   | 1.2957          | 37.9416 | 13.6739 |
| 0.8989        | 0.3529 | 60   | 0.5241          | 24.9348 | 9.3570  |
| 0.3737        | 0.5294 | 90   | 0.3112          | 18.8135 | 6.9347  |
| 0.2528        | 0.7059 | 120  | 0.2354          | 13.5640 | 5.0195  |
| 0.1989        | 0.8824 | 150  | 0.2011          | 13.6989 | 7.9763  |
| 0.1554        | 1.0588 | 180  | 0.1727          | 10.2742 | 4.3784  |
| 0.1106        | 1.2353 | 210  | 0.1610          | 9.3393  | 3.5788  |
| 0.0918        | 1.4118 | 240  | 0.1560          | 12.3236 | 6.5779  |
| 0.0913        | 1.5882 | 270  | 0.1520          | 11.1640 | 5.3914  |


### Framework versions

- Transformers 4.45.1
- Pytorch 2.4.1+cu124
- Datasets 3.0.1
- Tokenizers 0.20.0